The work described in this thesis is concerned with self-localisation (automated estimation of sensor locations) and source-localisation (location of a target) using Wireless Sensor Networks (WSNs). The motivation for the research in this thesis is the on-line localisation of marmots from their alarm calls. The application requires accurate 3D self-localisation (within a small percentage of sensor spacing) as well as timely operation. Further challenges are added by the high data-rate involved: sensor nodes acquire data at a rate that is greater than the available network bandwidth. This data cannot be streamed over a multi-hop network, implying a need for data reduction through in-network event detection and local data compression or filtering techniques. The research approach adopted in this thesis combined simulation, emulation and real-life experimentation. Real-life deployment and experimentation highlighted problems that could not be predicted in controlled experiments or simulation. Emulation used data gathered from controlled, real-life experimentation to simulate proposed system refinements; this was sufficient to provide a proof-of-concept validation for some of the concepts developed. Simulation allowed the understanding of underlying theoretical behaviour without involving the complex environmental effects caused by real-life experimentation. This thesis details contributions in two distinct aspects of localisation: acoustic ranging and end-toend deployable acoustic source localisation systems. With regard to acoustic ranging and 3D localisation, two WSN platforms were evaluated: one commercially available, but heavily constrained (Mica2) and one custom-built for accurate localisation (Embedded Networked Sensing Box (ENSBox)). A new proof of concept platform for acoustic sensing (based on the Gumstix single-board computer) was developed by the author (including the implementation of a ranging mechanism), based on experiences with the platforms above. Furthermore, the literature was found to lack a specific procedure for evaluation and comparison of self-localisation algorithms from theoretical conception to real-life testing. Therefore, an evaluation cycle for self-localisation algorithms that encompassed simulation, emulation and real-life deployment was developed. With respect to source localisation, a hardware and software platform named VoxNet was designed and implemented.

Network growing mechanisms are used to construct random networks that have structural behaviors similar to existing networks such as genetic networks, in efforts of understanding the evolution of complex topologies. Popular mechanisms, such as preferential attachment, are capable of preserving network features such as the degree distribution. However, little is known about such randomly grown structures regarding robustness to disturbances (e.g., edge deletions). Moreover, preferential attachment does not target optimizing the network's functionality, such as information flow. Here, we consider a network to be optimal if it's natural functionality is relatively high in addition to possessing some degree of robustness to disturbances. Specifically, a robust network would continue to (1) transmit information, (2) preserve it's connectivity and (3) preserve internal clusters post failures. In efforts to pinpoint features that would possibly replace or collaborate with the degree of a node as criteria for preferential attachment, we present a case study on both; undirected and directed networks. For undirected networks, we make a case study on wireless sensor networks in which we outline a strategy using Support Vector Regression. For Directed networks, we formulate an Integer Linear Program to gauge the exact transcriptional regulatory network optimal structures, from there on we can identify variations in structural features post optimization.

L’Internet des objets amène des contraintes uniques et une immense variété d’applications. Ceci oblige à être capable d’établir des communications efficaces en énergie (et néanmoins à faible délai) au sein de réseaux fortement dynamiques. Nous nous sommes concentrés sur l'amélioration du contrôle d'accès au medium (MAC), afin d’optimiser la gestion des communications sans fils,principale source de consommation d'énergie dans ces réseaux. Cette thèse discute de l’auto adaptation de solutions MAC asynchrones et montre qu’une coopération localisée entre objets communicants permet de maintenir un partage efficace de la ressource de communication face à une forte dynamique (trafic, mobilité, pannes). Outre une réflexion menée sur les outils de simulation et d'expérimentation, nous avons conduit des campagnes d'évaluations complètes de nos contributions qui traitent tant des changements de trafic que de la mobilité dans les réseaux très denses. / The Internet of Things brings unique constraints and a huge variety of applications. This forces to be able to establish energy efficient communications (and never the less low-delay) within highly dynamic networks. We focused on improving the medium access control (MAC) to optimize the management of wireless communications, the main source of energy consumption in these networks. This thesis discusses the self-adaptation of asynchronous MAC solutions and shows that a localized cooperation between communicating objects can maintain an efficient sharing of the communication resource in highly dynamic networks (traffic, mobility, failures). In addition to a reasoning on the tools of simulation and experimentation, we conducted comprehensive evaluation campaigns of our contributions that address traffic changes and mobility in dense networks.